Understanding how mutations arise is fundamental for the understanding of evolution of the living systems. However, all methods currently used to detect mutations, i.e., phenotypes assays and whole genome sequencing, are affected by fitness effects of newly arisen mutations. Deleterious and beneficial mutations decrease and increase frequency of mutants, respectively, which renders impossible to correctly measure mutation rates. To solve this problem, we developed mutation assay based on the activity of the E. coli mismatch repair system, which detects emerging mutations independently of their future effect on phenotype: beneficial, neutral, deleterious, or even lethal. The MutS mismatch protein detects diverse base pair mismatches, while MutL protein interacts with MutS–mismatch complex and triggers removal of the mutation from the newly synthesized strand. We showed that tagging MutL protein with fluorescent protein allows monitoring DNA replication errors in single living cells (Elez et al; 2010 and 2012). This assay allowed us to precisely measure mutation rates at a single cell level and to show that most spontaneous DNA replication errors in proliferating cells arise in subpopulations of cells suffering endogenous stresses (Woo et al; 2018). In order to learn how genome structuration impacts the emergence of spontaneous mutations, we intend to establish mutational topology of E. coli genome, i.e., to map distribution of the hypo- and hyper-mutable sites. We will establish if mutation distribution correlates with the genome structuration in macrodomains, GC content, gene transcription levels, DNA replication-transcription direction collinearity, gene essentiality, etc. For this, we will perform Chip-Seq analysis of MutL protein in different genetic backgrounds and different growth conditions. Such harnessing of the natural mutation detection proteins, MutS and MutL, will allow us to establish an unprecedented unbiased genome wide mutational profiles.
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